Molecular techniques can be employed to detect and map the chromosomal locations of genes contributing to variation in growth, feed intake, energetic efficiency, feeding behavior, and carcass merit. Several molecular tools and approaches, as well as statistical and computational techniques, are available that can be employed to quantify the number(s), location(s) and effect(s) of quantitative trait loci (QTL) through the use of genotypic information from genetic markers that are evenly spaced along chromosomes in the genome. A QTL is defined as the chromosomal location of individual or groups of genes, of unknown primary function, that show(s) significant association with a complex trait of interest (Lander and Kruglyuak, 1995, Natural Genet 11: 241-247). In beef cattle, QTL have been detected for disease tolerance (Hanotte et al., 2003, PNAS Agricultural Sciences 100:7443-7448), fertility and reproductive performance (Kirkpatrick et al., 2000, Mammalian Genome 11:136-139), body conformation (Grobet et al., 1998, Mammalian Genome 9: 210-213), birth weight and growth performance (Davis et al., 1998, Proc. 6th World Congr. Genet. Appl. Livest. Prod. 23: 441-444; Casas et al., 2003, J. Anim. Sci. 81, 2976-83; Li et al., 2002, J. Anim. Sci. 80:1187-1194; Kim et al., 2003, J. Anim. Sci 81, 1933-42), and carcass and meat quality (Keele et al., 1999, J. Anim. Sci 77. 1364-1371; Casas et al., 2000, J. Anim. Sci. 78:560-569; MacNeil and Grosz, 2002, J. Anim. Sci. 80:2316-2324; Casas et al., 2003; supra; Kim et al., 2003, supra: Moore et al., 2003, J. Anim. Sci. 81:1919-1925; and Li et al., 2004, J. Anim Sci. 2004 82: 967-972).
It is possible to search for and identify associations between polymorphisms in specific candidate genes and measures of variation in feed intake, feed efficiency and feeding behavior. A candidate gene may be selected based on previously known biochemical or physiological information or may be chosen because it maps to or close to the location of a QTL (positional candidate gene). Of interest among these candidates are genes shown to affect feed intake, behavior, energy balance, and body composition.
Several polymorphisms in candidate genes have been shown to be associated with economically relevant traits in beef cattle (e.g., Chrenek et al., 1998, Czech Journal of Animal Science 43, 541-544; Barendse et al., 2001, “The TG5 DNA marker test for marbling capacity in Australian feedlot cattle.” on the worldwide web at beef.crc.org.au/Publications/MarblingSym/Day1/Tg5DNA: Ge et al., 2001, J. Anim. Sci. 79:1757-1762; Grisart et at, 2002. Genome Research 12:222-231; Buchanan et al., 2002; Genet. Sel. Evol. 34:105-116: Moore et al., 2003, J. Anim. Sci. 81:1919-1925; Li et al., 2004, supra; and Nkrumah et al., 2005, J. Anim. Sci. 83:20-28).
Likewise, several polymorphisms in candidate genes have been shown to be associated with economically relevant traits in dairy cattle (e.g., Blott, et al., (2003) Genetics 163:253-66; Cohen-Zinder, et al., (2005) Genome Research 15:936-44; Grisart, et al., (2004) Proc Natl Acad Sci USA 101:2398-403; Khatib, et al., (2007) J Anim Breed Genet 124:26-8; Khatib, et al., (2007) J Dairy Sci 90:2966-70; Khatkar, et al., (2004) Genet Sel Evol 36:163-90; Kubarsepp (2005) Agronomy Research 3:55-64; Olsen, et al., (2007) BMC Genet 8:32: Tsiaras, et al., (2005) J Dairy Sci 88:327-34; and Weikard, et al., (2005) Physiol Genomics 21:1-13).
Cattle are an important food source, both for their milk and meat. There is increasing interest in identifying the genetic basis for the fat content of milk from dairy cows and the marbling pattern of meat from dairy and beef cattle. The present invention meets these and other needs.